1. Field of the Invention
The present invention relates to two-dimensional gas chromatography analysis. In particular, the invention is a method for quantitative analysis of petroleum samples by two-dimensional gas chromatography.
2. Description of the Prior Art
Two-dimensional gas chromatography (2D GC) is a particularly efficient separation technique for performing detailed molecular analyses. This well-known technique is for example described in U.S. Pat. Nos. 5,135,549 and 5,196,039. These patents describe the principle of continuous coupling of two different separation columns in order to obtain two-dimensional chromatograms.
Two-dimensional gas chromatography is a separation technique wherein all the eluted compounds of a first column are successively subjected to a separation in a second column of different selectivity. The two columns are connected in series by means of a modulator that is the key element of the device. This interface samples the effluent of the first column in a form of chemical impulses and it transfers them to the second column. The time required for performing this operation, referred to as modulation period, generally requires a very fast (some seconds) second separation: the characteristics of the second column are selected in such a way that each impulse is separated during the modulation period. FIG. 1 diagrammatically shows the principle of 2D-GC.
The more affinity the compound has with the stationary phase, the more time it will need to leave each column. At the outlet of the second column, the compounds encounter a detector. This device measures various physical properties of the gaseous mixture in its form of an intensity as a function of time. This signal, referred to as chromatographic signal or “raw 1D” signal, comprises a set of peaks, characteristic of each constituent, whose shape depends on the intensity of the property measured. Each peak is called “elution peak” or “chromatographic peak”. The maximum intensity corresponding to a peak is referred to as retention time. The signal thus recorded can be of different nature depending on the detector used. The detectors (TCD, FID, SCD, NCD, . . . ) are selected according to the application type by the person skilled in the art.
Some detectors allow detection of ppm (parts per million) of a component.
The elution peak from the first column is periodically sampled by the modulator. Each fraction is focused, then continuously injected into the second column. The detected chromatographic signal, the raw 1D signal, thus corresponds to a succession of separations (materialized by peaks on the signal) carried out in the second dimension. By combining these chromatograms with an offset, it is possible to reconstruct a signal in two dimensions: the beginning of each modulation cycle marks the retention time of a compound in the first dimension, whereas the maximum of each peak marks the retention time in the second dimension. An offset has to be introduced for the retention order in the second dimension to be correct. It allows shifting all the retention times on the ordinate axis by a constant value. This operation is useful to correctly represent the structure of a chromatogram wherein the absolute secondary retention time (that is on the y-axis) of a compound is greater than the modulation period, provided that the retention time difference between the less retained compound and the most retained compound is smaller than the modulation period (that is absence of separation overlap, or wrapping around).
The result can come in a form of a three-dimensional chromatogram, two of the axes representing the retention times on each of the separation dimensions, and the third axis indicating the intensity of the signal (3D in FIG. 1). The commonest representation is two-dimensional (2D chromatogram) wherein the two axes of the separation plane indicating the temporal coordinates. The chromatographic peaks (elution peaks) then form spots whose intensity is shown by a color gradation. This representation is close to a molecular image of the sample. In the example shown in FIG. 1, two solutes co-eluted after the first separation are separated during the second separation, provided that the nature of the stationary phases coating each column is suited thereto.
However, the results obtained from a two-dimensional gas chromatography (2D-GC) have to be coupled with complex data analysis methods.
As in conventional GC (gas chromatography), quantification of a solute in 2D-GC is carried out by calibrating the response of the detector by the measurement of the surface area of the elution peak. In the specific case of 2D-GC, the chromatogram is generally represented in a form of an iso-response surface that has to be integrated to obtain the volume of an elution peak proportional to the amount of solute introduced. As mentioned in the publication below, there are three known types of two-dimensional gas chromatography (2D-GC) quantitative analyses. All these methods are based on the definition of zones delimiting the spots representative of the elution peaks. These zones are referred to as “blobs” by specialists.    Van Mispelaar V. G. et al., 2005, “Novel System for Classifying Chromatographic Applications, Exemplified by Comprehensive Two Dimensional Gas Chromatography and Multivariate Analysis”, Journal of Chromatography A., 1071 (2005) pp. 229-237.1—Determination of the Concentrations of a Certain Number of Predefined CompoundsThe compounds are identified by their retention times on the two axes (that is the maximum time of a zone). The surface area of the zone is converted to concentration by calibration. A clear return to the base line between two zones is assumed in this analysis. The base line corresponds to the signal recorded in the absence of compounds (that is in the presence of the mobile phase alone).2—Determination of the Concentrations of Peak GroupsFor some applications, the number of peaks is tens of thousands with strong co-elutions. It is then practically impossible to identify each peak individually. The goal is to group them together according to pseudo-components having common chemical or structural properties (same chemical type (structural homologs) with the same number of carbon atoms, the same number of double bonds, and the same number of aromatic rings, etc.).3—Determination of the Similarities and Differences Between Several AnalysesThe goal is to automatically determine the differences in terms of presence and concentration of compounds. Image processing and classification techniques are used. These techniques are used in particular for follow-up analyses or for sample screening, while disregarding the analytical details.
There are three types of operating methods for implementing this type of analysis.
Mode 1. The principle is as follows:
Definition of a generic mask of contour zones for each constituent (or blob) for an image type. Meta-data (name of the component, properties of the component) are possibly added.
Application of the mask to a new image.
Manual modification of the blobs to determine the exact position in the new image of each contour so as to take account of (i) the experimental uncertainties and of (ii) the variations linked with the concentration of the constituents.
This operating method is provided in the software GC Image® (Zoex, USA). This operating method is difficult to apply: in fact, the definition of the contour zones of each blob greatly depends on the user and on the way the individual peaks are defined from the complete image. The method is therefore neither very accurate nor very repeatable.
Mode 2. The principle is as follows:
Automatic determination of all the peaks of the image by image analysis
One-to-one association of a peak with a blob
Manual assignment of a chemical compound for each blob.
This operating method is described in the publication below. The peaks are determined directly in the image by means of a watershed type algorithm.    S. E. Reichenbach, V. Kottapalli, M. Ni, A. Visvanathan, 2005, Computer Language for Identifying Chemicals with Comprehensive Two-Dimensional Gas Chromatography and Mass Spectrometry, Journal of Chromatography, Vol. 1071, pp. 263-269.
This method is not suited to analysis of type 2 because the number of peaks is too large (several thousands). It is then impossible to assign a component to each peak. Furthermore, the implicit assumption of one-to-one relation between a blob and a peak is wrong: a blob often consists of several peaks.
Mode 3. The principle is as follows:
Automatic determination of all the peaks of the image
Identification of the peaks by rules. This operating method is described in the following publication:    M. Ni, S. E. Reichenbach, A. Visvanathan, J. TerMaat, E. B. Ledford, 2005, Peak Pattern Variations Related to Comprehensive Two-Dimensional Gas Chromatography, Journal of Chromatography, Vol. 1086, pp. 165-170. Setting up the rules is complicated.
Mode 4. The principle is as follows:
Automatic determination of all the peaks of the raw 1D signal (SB) corresponding to the image by conventional integration (1D GC techniques).
Definition of zones (blobs) in the image by the user.
The final surface area of the blob corresponds to the sum of the surface areas of the peaks of the raw 1D signal (SB) belonging to the blob.
This operating method is provided by the software HyperChrom® (Thermo, USA).    Daniela Cavagnino, Paolo Magni, Giacinto Zilioli, Sorin Trestianu, 2003, Comprehensive Two-Dimensional Gas Chromatography Using Large Sample Volume Injection for the Determination of Polynuclear Aromatic Hydrocarbons in Complex Matrices, Journal of Chromatography A, 1019 (2003) 211-220.
This method however involves the following drawbacks:
It is not possible to define a mask predefining several blobs to be applied for each new analysis (pattern). For each new analysis, the user has to define a new mask, which is costly in analysis time and operator-dependent.
A blob is necessarily a predefined quadrilateral that can be deformed thereafter. Some blobs therefore cannot be correctly positioned for correctly trimming each elution peak. Now, according to type 2, it must be possible to define zones corresponding to several hundred peaks whose contour can be very tortuous.
In case of strong co-elutions, it can be very difficult to precisely define the elution peaks in the secondary chromatogram corresponding to the second separation. In this case, the proposed integration is generally erroneous because the zone to be integrated from the blob is not well defined. There is no a posteriori control in case of absence of detection of a peak.
The user cannot really visualize the limits of each blob.
Mode 5. The principle is as follows:
Definition of a mask of zones (blob) in the image
Automatic determination of all the peaks of the image
Assignment of the previously defined peaks to the blobs via statistical analyses.
This operating method is described in the following publication:    M. Ni, S. E. Reichenbach 2005, Using Edge Pattern Matching for Automatic Chemical Identification in GC 2D, Automatic Target Recognition XIV. Edited by Sadjadi, Firooz A. Proceedings of the SPIE, Volume 5426, pp. 155-163 (2004).
The adjustment between the images is performed peak by peak. The authors reduce the data by working only on the peak maximum. However, they implicitly assume a one-to-one relation between a peak and a blob (and therefore a chemical component). This is not the case in practice. Furthermore, the method provided greatly depends on the chemical composition of the product. Since a blob can contain several peaks whose concentration ratio can vary, the maximum of a blob can be very variable.
In short, two-dimensional gas chromatography is a particularly efficient technique that is used in the industry to carry out quantitative analyses of samples such as petroleum samples for example. This technique however involves complex analysis methods. Current analysis methods are not entirely satisfactory:
the definition of polygons defining the spots in the image is sometimes difficult because the number of peaks is very large. These zones can also involve several peaks,
identification of the zones (blobs): associating a chemical compound with a zone is delicate. The larger the number of carbon atoms, the larger the number of isomers. It is then delicate to associate a component with a peak.
Furthermore, these methods of analyzing two-dimensional gas chromatography (2D GC) results are manual and they therefore have two major drawbacks: they require much time and their results depend on the interpreter. Such analyses are therefore difficult to use in practice because of their inaccuracies. Because the number of polygons is general above 150, automated methods have to be applied.